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Research on Uncertain Programming Model for Emergency Response Missions to Catastrophes

Author: LiYingXiong
Tutor: LiXiangYang
School: Harbin Institute of Technology
Course: Management Science and Engineering
Keywords: scenario-response emergency response mission chanceconstraint programming oversubscribed programming bi-level programming
Type: PhD thesis
Year: 2013
Downloads: 161
Quote: 0
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Since the beginning of history, human shouldn’t only devotes themselves intodevelopment and liberation of the productive forces, the promotion of socia l andhuman, but also must struggle with all kinds of hazards, especially catastrophicevents. Catastrophic events have caused enormous economic losses, mass casualties,infrastructure damage. Recently, catastrophic events have been one of the mainthreats to the human society, has been the social problem of human. Catastrophicresponse could work effectively to reduce the losses caused by catastrophic events,to avoid unnecessary casualties, and to save property of country and people,therefore catastrophic response have been highly concerned by the society politicsand scientists; the whole society hope to make great progress in catastropheresponse.Catastrophic events have low frequency and litter or no sign, bring about adisastrous impact on society; they are "heavy impacting event with smallprobability". The existing resources and ability cannot meet the demand ofemergency response, conventional emergency response mechanism is not applicableto the catastrophic response task, and this has brought huge challenge ofcatastrophic researchers and response staff. catastrophe response have manyuncertainty, this is one of the biggest difference between catastrophe response taskand general disaster response task; catastrophic events rarely appear or do notappear signs, so the catastrophe response decis ion time is very short, resulting incatastrophic response task decis ion information is not suffic ient.The main object is the natural disaster catastrophe events, the main researchcontent is to deal with the problem of mission planning in the state of emergencyresponse after catastrophic events outbreak. Based on the review and summary ofthe existing research results, catastrophe task is decomposed into fie ld-levelmissions and basic-level missions. using uncertainty theory and uncertainprogramming theory, uncertainty characters of catastrophe response have beendiscussed; and then value function of catastrophe response missions have beenstudied; on this basis, uncertainty programming model for field-level missionsystem, basic-level mission and bi-level programming model for catastropheresponse missions are built.Because of the shortage of emergency resources and capabilities, theoversubscribed programming models are built. For reference the oversubscribedplanning problems study in the fie ld of engineering technology, this researchestablishes the mathematical model of oversubscribed programming problems, and extended to uncertain oversubscribed programming model.At first, it establishes catastrophe response miss sons system in thisdissertation. Based on the catastrophe response mission decomposing practices, thedouble-level catastrophe response missions are constructed in this dissertation,fie ld-level missions system and basic-level missions system. The field-levelmissions are aimed at upper or high response organization(or commanders) to dealwith the tasks; it is macro-layer and professional missions; its main contents includetask over-planning mission, resource allocation mission and execution&coordinated missions; basic-level missions are aimed to deal with the task atbase-layer, refers to deal with tasks in basic-level, at the scene; its main contentinclude emergency rescue missions, disaster control missions and livelihoodrecovery missions. This research also discusses the logic relation and time orderrelationship between each response missions.The second, value function of catastrophe response missions is constructed.After studying the uncertain attribute of catastrophe response missions, according touncertain statistics method, uncertain variables for catastrophe response missionsare generated. Because of the uncertain characteristics of catastrophe responsemissions, value function of catastrophe response mission is constructed, and thenplanning objectives are to maximizing value function. The reference point of valuefunction is expectations amount of emergency resources and capabilities; ifemergency resources and capabilities supplied are more than reference point, thedifference between them are defined as "incomes" of catastrophe response missions;else defined as "losses". The catastrophic response missions are by value function.The third, programming model system for catastrophe response missions isestablished. According to the uncertain planning theory and oversubscribedprogramming model established, uncertain programming models for catastropheresponse missions are built, including field-level missions programming models andbasic-level missions programming models. fie ld-level missions programmingmodels are formed by task overall programming models, resource allocationprogramming models and transportation support mission programming models; andbasic-level missions programming models are formed by temporary power supplymissions programming models, power-hub repair missions programming modelsand power-network repair missions programming models.At fourth, bi-level programming model for catastrophe response missions isestablished. Field-level missions programming models and basic-level missionsprogramming models are integrated into bi-level programming model forcatastrophe response missions, using process model integration method. And then,Stachelberg-Nash equilibrium solution algorithm of bi-level programming model isdiscussed. Finally, a realistic case by large area power grid damage cause by catastrophicevents in china is designed; and then application of uncertain programming modelfor catastrophe response missions is introduced, the usefulness and practicality isdemonstrated.

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CLC: > Environmental science, safety science > Disasters and their prevention
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